Collaborative tagging as a tripartite network

TL;DR

This paper models online collaborative communities as tripartite networks of persons, items, and tags, using projection and percolation techniques to reveal community structures and diversity within the system.

Contribution

It introduces a novel tripartite network framework and projection methods to analyze community structures and diversity in collaborative tagging systems.

Findings

Identification of community structures through network projection

Use of percolation techniques to analyze network connectivity

Visualization of network structures with tree representations

Abstract

We describe online collaborative communities by tripartite networks, the nodes being persons, items and tags. We introduce projection methods in order to uncover the structures of the networks, i.e. communities of users, genre families... To do so, we focus on the correlations between the nodes, depending on their profiles, and use percolation techniques that consist in removing less correlated links and observing the shaping of disconnected islands. The structuring of the network is visualised by using a tree representation. The notion of diversity in the system is also discussed.